internal medicine clinic optimization 1 graduate ... · supplementary notes ... internal medicine...

Internal Medicine Clinic Optimization 1

Running head: INTERNAL MEDICINE CLINIC OPTIMIZATION

Graduate Management Project

Optimizing The Internal Medicine Clinic at

Evans Army Community Hospital

Major Jose A. Bonilla

U.S. Army-Baylor University Graduate Program in Healthcare

Administration

A paper submitted in partial fulfillment of the

requirements for the U.S. Army-Baylor University Graduate

Program in Healthcare Administration

2003

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1. REPORT DATE JUL 2003

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4. TITLE AND SUBTITLE Optimizing The Internal Medicine Clinic at Evans Army Community Hospital

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6. AUTHOR(S) Major Jose A. Bonilla

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7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Evans Army Community Hospital Ft Carson, CO 80913

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9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) US Army Medical Department Center and School Bldg 2841 MCCS-HRA(US ArmyBaylor Program in HCA) 3151 Scott Road, Suite 1412 FortSam Houston, TX 78234-6135

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14. ABSTRACT Although the Department of Defense (DoD) has established access to care standards for military healthcare organizations and their treatment facilities, many facilities may face challenges in meeting thesestandards. In fiscal year (FY) 2002, the Internal Medicine (IM) clinic at Evans Army Community Hospital,Fort Carson, Colorado, failed to meet access to care standards for routine appointments, and was onlymarginally successful in meeting standards for urgent appointments. Because of the inextricable link withoptimization and access to care, this study is an initiative that utilizes business operational analysis in aneffort to optimize operations and maximize access to care to the beneficiaries enrolled in the InternalMedicine clinic. The results of this study suggest that by reorganizing primary care managers (PCMs)empanelment, reassessing the full time equivalent (FTE) for each PCM, improving the provider to supportstaff ratios, and improving providers template management, access to care will be substantially improvedfor enrolled beneficiaries.

15. SUBJECT TERMS Optimization; Linear Programming; Enrollment Capacity; Access to Care; Internal Medicine

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UU

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67

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a. REPORT unclassified

b. ABSTRACT unclassified

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Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18


Acknowledgements

There are many people that I would like to acknowledge in

the preparation of this Graduate Management Project. First, I

would like to thank my reader/advisor LTC Christopher Pate and

my preceptor LTC Steven Chowen for all their assistance this

past year. Second, the staff of the Evans Army Community

Hospital, Fort Carson, Colorado, especially LTC(P) Leo Tucker,

COL Scott Goodrich, Mr. Tim Jordan, Mr. Butch Huffstetler, CPT

Noel Pace, Ms. Denise Downs, and Ms. Zoraida Perez for without

their help I would have never finished this project. I would

like to thank LTC George Patrin from MEDCOM for providing me

with invaluable advice on the primary care optimization process.

I also need to thank my wife and family for all their support

throughout this program. Without your help, I would have never

made it through. Lastly, I would like to thank MAJ Ellen Daly,

the former Baylor Resident, for helping me in transitioning into

the facility and providing invaluable advice in completing this

project.


Abstract

Although the Department of Defense (DoD) has established access

to care standards for military health care organizations and

their treatment facilities, many facilities may face challenges

in meeting these standards. In fiscal year (FY) 2002, the

Internal Medicine (IM) clinic at Evans Army Community Hospital,

Fort Carson, Colorado, failed to meet access to care standards

for routine appointments, and was only marginally successful in

meeting standards for urgent appointments. Because of the

inextricable link with optimization and access to care, this

study is an initiative that utilizes business operational

analysis in an effort to optimize operations and maximize access

to care to the beneficiaries enrolled in the Internal Medicine

clinic. The results of this study suggest that by reorganizing

primary care managers’ (PCMs) empanelment, reassessing the full

time equivalent (FTE) for each PCM, improving the provider to

support staff ratios, and improving providers’ template

management, access to care will be substantially improved for

enrolled beneficiaries.


Table of ContentsAcknowledgements . . . . . . . . . . . . . . . . . . . . . 2

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . 3

Introduction . . . . . . . . . . . . . . . . . . . . . . . 8

Conditions Which Prompted the Study . . . . . . . . . . 8

Statement of the Problem . . . . . . . . . . . . . . . 10

Literature Review . . . . . . . . . . . . . . . . . . . 13

Purpose . . . . . . . . . . . . . . . . . . . . . . . . 21

Methods and Procedures . . . . . . . . . . . . . . . . . . 22

Supply of Care. . . . . . . . . . . . . . . . . . . . . 24

Innova Group Analysis.. . . . . . . . . . . . . . . . . 24

Estimated Supply of Care . . . . . . . . . . . . . . . .24

Support Staff and Exam Rooms Ratios . . . . . . . . . . 25

Linear Programming Model... . . . . . . . . . . . . . . 25

Provider Productivity . . . . . . . . . . . . . . . . . 26

Demand for Care . . . . . . . . . . . . . . . . . . . . 26

Enrollment Capacity . . . . . . . . . . . . . . . . . . 26

Estimated Demand for Care and Beneficiary Visits. . . . 27

Appointment Wait Time and Access to Care Metric . . . . 28

Data Sources . . . . . . . . . . . . . . . . . . . . . 29

Results . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Supply of Care . . . . . . . . . . . . . . . . . . . . 30

Innova Consulting Group Results . . . . . . . . . . . . 30

Estimated Supply of Care . . . . . . . . . . . . . . . 32

Support Staff and Exam Room Ratios. . . . . . . . . . . 33

Linear Programming Model . . . . . . . . . . . . . . . 35

Provider Productivity . . . . . . . . . . . . . . . . . 38


Demand for Care . . . . . . . . . . . . . . . . . . . . 39

MEDCOM Enrollment Capacity Model . . . . . . . . . . . 39

Estimated Beneficiary Visits per Year . . . . . . . . . 41

Estimated Demand for Care . . . . . . . . . . . . . . . 42

Appointment Wait Time.. . . . . . . . . . . . . . . . . 43

Template Management . . . . . . . . . . . . . . . . . . 43

Access to Care Metric. . . . . . . . . . . . . . . . . .44

Discussion . . . . . . . . . . . . . . . . . . . . . . . . .45

Recommendations . . . . . . . . . . . . . . . . . . . . . . 51

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . .55

References . . . . . . . . . . . . . . . . . . . . . . . . .57

Appendix Primary Care Optimization Business Case Analysis 60


List of Tables

Table 1. Internal Medicine Clinic Average Provider

Availability in FY 2002 . . . . . . . . . . . . . . 31

Table 2. Primary Care Clinics Average Support Staff to Provider

Ratios in FY 2002 . . . . . . . . . . . . . . . . . 34

Table 3. Primary Care Clinics Average Exam Room to Provider

Ratios in FY 2002 . . .. . . . . . . . . . . . . . . 35

Table 4. Primary Care Clinics Average Relative Value Units in

FY 2002 . . . . . . . . . . . . . . . . . . . . . . 38

Table 5. MTF Average Relative Value Units Comparison in

FY 2002 . . . . . . . . . . . . . . . . . . . . . . 39

Table 6. IM Clinic Average Enrollment Capacity by Beneficiary

Category in FY 2002 . . . . . . . . . . . . . . . . .40

Table 7. Primary Care Clinics Average Enrollment Capacity by

Beneficiary Category in FY 2002 . . . .. . . . . . 41

Table 8. Average Beneficiary Visits in Internal Medicine Clinic

FY 2002 by Category . . . . . . . . . . . . . . . . 42

Table 9. FY 2002 Access to Care Metric Results . . . . . . . 44


List of Figures

Figure 1. Current and Proposed Hospitalist Schedule . . . . 32

Figure 2. Linear Programming Appointment Model . . . . . . 37


Introduction

Conditions which prompted the study

Although the Department of Defense (DoD) has established

access to care standards for military health care organizations

and their treatment facilities, many facilities may face

challenges in meeting these standards. In fiscal year (FY) 2002,

the Internal Medicine (IM) clinic at Evans Army Community

Hospital, Fort Carson, Colorado failed to meet access to care

standards for routine appointments, and was only marginally

successful in meeting standards for urgent appointments. In the

period between March and August 2002, the IM clinic met

appointment access standards only 65% of the time for acute

appointments and 21% of the time for routine appointments.

Changes in TRICARE to extend coverage to the over the age

of 65 population have resulted in the creation of TRICARE Senior

Prime. TRICARE Senior Prime was a managed care demonstration

program designed to better serve the medical needs of military

retirees, dependents, and survivors who are age 65 and over. The

evolution of this managed care demonstration program and

continuing efforts to accommodate TRICARE Senior Prime age-ins

(beneficiaries turning age 65 between January 1 and December 31,

2002) has critically impacted the capacity of each primary care

manager (PCM) in the IM clinic. The demonstration program ended


in December 2001 and beneficiaries participating in the program

were enrolled in the new program called TRICARE Plus.1 Currently,

over 2,300 of these beneficiaries are enrolled in the IM clinic:

an enrollment figure that represents approximately 32% of the

total enrolled population in the IM clinic.

Historically, the age 65 and over population presents more

complex medical conditions, which require more direct care time

from the PCM in almost every visit. Consequently, this

population is affecting the ability of the IM clinic to meet

access to care standards due to prolonged patient visits, which

in turn limits the number of appointments available to other

beneficiaries.

In February 2001, EACH received approval for an

optimization initiative for its primary care clinics. The

hospital received a total of $1.3 million for primary care

optimization (PCO) projects. The February 2001 PCO initiative

only addressed shortages in providers and support staff of all

three primary care clinics (Internal Medicine, Family Practice,

Pediatrics), the Emergency Department and the Primary Acute Care

1 TRICARE Plus is a primary care enrollment program open to

beneficiaries who are eligible for care in military treatment

facilities (MTFs).


Clinic (PACC). Because of the interdependence between these

organizational elements, a more detailed analysis of each

primary care clinic is necessary in order to develop a plan to

effectively allocate $1.3 million on primary care optimization

initiatives. The Internal Medicine clinic is the first clinic

identified for this initiative.

Statement of the problem

The Internal Medicine clinic primary care optimization plan

became a top command priority as a result of the decrease in

access and the saturated appointment system. In FY 2002, the IM

clinic at EACH failed to meet access to care standards for

routine appointments, and was only marginally successful in

meeting standards for urgent appointments. The Medical Command’s

(MEDCOM) access to care goal is 90% or higher compliance for

urgent and routine appointments. In FY 2002, the IM clinic

failed to meet access to care standards 11 out of 12 months for

urgent appointments. During the same period, the compliance

rates in FY 2002 by month for urgent appointments ranged from

66% to 90%, and the IM clinic failed to meet access standards

for routine appointments. Compliance rates for routine

appointments in FY 2002 by month ranged from 32% to 82%. In

February 2001, EACH submitted a Primary Care Optimization (PCO)

Business Case Analysis (BCA) to the U.S. Army Medical Command


(MEDCOM) as an initiative to improve support staff ratios within

the primary care clinics (Appendix). The business case analysis

is an economic analysis used to evaluate the costs and benefits

of at least one alternative to the status quo. The PCO BCA only

addressed human resource shortages for improving access to

primary care services. A more deliberate and encompassing

optimization plan is needed to effectively address the IM

clinic’s access to care issues.

A personnel shortage in the IM clinic is also critically

affecting the clinic’s capability to sustain access to

healthcare services. By losing one military internist without an

authorized replacement, the IM clinic continues to saturate its

appointment schedules and place an unrealistic workload burden

on the current staff. The hiring of internists from the civilian

market has been a challenging task because of availability and

preferences of internists: a shortage of internists exists in

the labor market and many internists are unwilling to work in

the military health system. In fact, several hiring actions for

internists have been open for nearly 12 months.

Resource sharing agreements have been pursued to relieve

provider shortages in many specialties. Although use of these

providers improves the productive efficiency of the IM clinic,


regulations constrain the ability of the clinic to provide care

for all members of the enrolled population. Under TRICARE For

Life provider reimbursement systems, resource sharing providers

are paid from hospital operating funds, but are restricted from

seeing patients age 65 and over, which leaves this population

with access difficulties.

In October 2000, President Clinton signed the FY 2001 National

Defense Authorization Act (NDAA), Public Law 106-398. This law

brought many new initiatives to the TRICARE program including

TRICARE For Life benefits for the age 65 and over population.

TRICARE For Life is structured like a Medicare supplement and

acts as a secondary payer to Medicare claims. This newly

implemented program has significantly increased the demand for

appointments by the 65 and older population by approximately 40%

since TRICARE Senior Prime took effect in January 2002. Before

January 2002, the 65 and older TRICARE beneficiaries were

enrolled in TRICARE Senior Prime as part of the demonstration

program.

Partially because of TRICARE for life, the total number of

enrolled beneficiaries in the IM clinic jumped from 4,987 in

2000 to 7,094 in 2001. The total number of enrolled patients age

65 and over has steadily increased at an average rate of 20 to

23 patients per month. The increase in enrollment resulted in an


increase in appointment waiting times. Currently, a patient who

wishes to see his or her PCM for a routine appointment has to

wait approximately eight to ten days.

The lack of provider availability, insufficient supply of

appointments, and provider and support staff shortages, are

contributing factors affecting the ability of the IM clinic to

meet access to care standards. This project will examine,

identify, and make recommendations to improve beneficiary access

in the IM clinic.

Literature Review

The U.S. Army Medical Command (MEDCOM) and the TRICARE

Management Activity (TMA) are concerned about the increasing

costs of healthcare services being provided by the Managed Care

Support Contract (MCSC). In an attempt to save costs, MEDCOM and

TMA have ordered medical treatment facilities (MTFs) to optimize

their operations and work more efficiently in order to minimize

costly Bid Price Adjustments (BPA; Ardner, 2001).2

2 The BPA is what the government pays the MCSC for care

provided through the network. The BPA serves as a reconciliation

process between the MCSC and the Department of Defense (DoD)

where premium payments are continually updated to reflect

changes in the number of beneficiaries as well as increased

utilization of MCSC’s local network.


However, the trend over the last few years is that more

care is being provided by the MCSCs, and at a higher cost than

originally projected (Pace, 2001). TMA and MEDCOM assume that

healthcare delivered to patients in the MTF is more cost

effective than MCSC care provided in the network (Ardner, 2001).

In an effort to assist MTFs in working more efficiently,

maximizing productivity, and reducing costs, the U.S. Army

Surgeon General has mandated the development of the Balanced

Score Card (BSC) management system and the use of the Business

Case Analysis (BCA) approach to making business decisions by all

MEDCOM MTFs (Harben, 2001). Use of the BSC strategically and

operationally guides the AMEDD. Further, the BSC serves as a

means of fulfilling certain requirements established by the

Government Performance and Results Act (GPRA) of 1993,

particularly those related to performance analysis and

development of organizational strategies.

Evans Army Community Hospital’s primary care optimization

initiative supports the BSC initiatives. Optimization, as

defined in the AMEDD’s Population Health Clinical Optimization

Guide, is providing quality medical care by maximizing the right

resources at the right time. The PCO initiative categorically

meets the Fort Carson MEDDAC commander’s BSC initiatives which


include (a) access improvement, (b) alignment of resources with

changing mission and population, (c) planning for demand

changes, (d) maximization of total (MCSC and direct) system

efficiency, (e) delivering quality compassionate care, (f)

instilling a passion for eliminating wasted time and resources,

(g) improvement of MTF business process, and (h) effective

training for medical personnel. The implementation of the PCO

initiative will improve the efficiency of healthcare services

provided in the primary care arena and particularly the IM

clinic (COL S. Goodrich, personal communication September 18,

2002).

In December 2001, the Assistant Secretary of Defense for

Health Affairs, Dr. Thomas Carrato, set the foundation for the

military health system optimization plan. This foundation is

outlined in the first edition of the Population Health

Improvement (PHI) Plan and Guide. The PHI is the balancing of

awareness, education, prevention and intervention activities

required to improve the health of a specified population and

serves as a cornerstone of the DoD’s MHS Optimization Plan. At

the MTF level, PHI uses seven key process elements, which

include (a) identification of the population, (b) forecasting

demand, (c) managing demand, (d) managing capacity, (e)

providing evidence-based primary, secondary, and tertiary


prevention, f) community outreach, and (g) analysis of

performance and health status (DoD TRICARE Management Activity,

2001). The PHI’s seven key process elements are principles that

will guide the methodology employed in this research.

The PHI Plan and Guide presents a model for use in

predicting optimum enrollment capacity. The PHI’s historical

data illustrate that a military provider spends an average of

10% of his or her time on readiness-related tasks and spends 90%

on delivering direct patient care. Under the current guidance

published on the DoD PHI Plan and Guide, the goal is to enroll

1,300 to 1,500 beneficiaries per PCM (Helmers, 2001).

An enrollment capacity model developed by Helmers (2001)

suggests that the PHI model for enrollment capacity may not

fully consider real-world variables that affect the enrollee per

provider goal. The model developed through Helmers’ analysis

used medium sized MTFs and considered the actual costs of

military training, readiness, residency training, and indirect

patient care. This model suggests that military providers devote

more than 10% to readiness related activities (Helmers).

Aside from readiness considerations, an MTF’s capacity to

enroll its beneficiaries is affected by the following factors:

(a) the number of primary care managers (PCM), (b) PCM’s

availability to see patients, (c) patient demand for visits, and


(d) the productivity of providers. Additionally, these factors

are also influenced by the availability of support staff, space

for exam rooms, and leadership influence that encourages access

improvements (Bailey, 2000).

Access to health services is also affected by the size of

the calling population. As the size of the population increases,

the demand for health care services will also increase and

present monumental challenges in meeting access standards if

supply side factors do not accordingly adjust to changes in

demand.

Military health care organizations face challenges in

rapidly adjusting to changes in demand, and are particularly

challenged to procure an adequate number and an appropriate mix

of medical staff to meet primary care demands for the peacetime

beneficiary population (McGraw, Barthel, & Arrington, 2000).

Medical treatment facilities have a unique requirement, unlike

civilian healthcare facilities, of preparing providers and

support staff to meet a go-to-war mission: these readiness

considerations are critical in comparisons of private sector and

DoD productivity.

Productivity is also affected by the incentive structures

inherent in DoD compensation schemes. Military and civilian

physicians and the majority of support personnel within the MHS


are salaried employees. Davis (1999) showed that healthcare

organizations that are trying to increase productivity and

patient volume find that employed physicians lack sufficient

financial incentives and managerial skills to meet desired

productivity levels. Some of these healthcare organizations have

overhauled their physician compensation programs and introduced

effective incentives in order to increase physician productivity

(Davis, 1999).

In addition to establishing productivity-based incentives,

organizations have undertaken a number of initiatives to improve

productivity and efficiency. Tselikis (1996) and Zucker (1997)

propose several areas to focus effort to improving productivity:

1. Template management is the key to building a schedule

that is realistic and corresponds to what the provider is

actually doing. This includes appointment types and time

allocated to each appointment.

2. Analysis of proper support staff and physician

utilization is critical when developing daily tasks and

procedures. Physicians and support staff must perform tasks in

the least expensive way, and delegate tasks appropriately. In

other words, a clinic must know the roles and capabilities of

the clinical support staff to delegate tasks accordingly.

3. Proper staff mix is essential to maximize staff


utilization. Having the right personnel for the right job and

hiring physician assistants and nurse practitioners to perform

services that previously were conducted by physicians will

effectively reduce the need for hiring more physicians.

4. Maximize the utilization of technology to improve

processes and increase time allotted for patient-provider

interaction.

Murray and Berwick (2003) suggest that accessibility and

continuity of care are two key goals in any primary care

practice. Many primary care practices struggle to achieve these

goals mainly because of a seemingly overwhelming demand for

patient visits. Waits and delays in health care access have been

a challenge for many years and are partially due to overfilled

appointment schedules that require access reforms. Before

implementing an access reform in a primary care practice, the

clinic must have an understanding of the size of their patient

population, level of patient demand for visits, and number of

appointment slots available. These data can be calculated using

measures such as demand, capacity, panel size, and future open

capacity (Murray & Berwick).

Provider type may also affect accessibility and access to

care. Studies by Bertakis et al. (1998) show that internal

medicine primary care physicians, as compared with family


practice physicians, spend more time examining and instructing

patients, demonstrate a greater tendency to order laboratory

tests, and refer more patients to specialty care. These studies

also suggest that patients assigned to the internal medicine

clinic make more appointments, have a higher no-show appointment

rate, and visit the emergency room and acute care clinic more

frequently (Bertakis et al.). As the organization strives to

understand differences in productivity across primary care

clinics, these observations have significance for EACH as it

attempts to improve productive efficiency in the IM clinic.

Understanding the relationship between provider types,

productivity, and population demographics is critical for making

decisions about what services to provide, how to provide them,

and for whom the services are offered. Many studies focusing on

these types of relationship have used quantitative techniques,

such as linear programming, to inform the decision making

process. Rothstein (1973) studied methods of allocating hospital

manpower in housekeeping operations. Starting with an agreed set

of desirable objectives, he developed a linear programming model

for the scheduling of hospital manpower with the goal of

maximizing the number of weekly assignments with the minimum

work force available. Similarly, Feldstein (1962) developed a

linear programming model in the pursuit of a desirable mix of


patients or cases to be treated. The model maximized the

weighted sum of the number of cases in each of nine medical

specialties, subject to constraints on such resources as bed

days, doctors and nurses. Dowling (1970) used a linear

programming model to determine the mix and volume of patients

that maximizes the total number of patients treated in a given

time period, subject to constraints on departmental capacities

and minimum patient requirements (Dowling, 1970). Smith, Over,

Hansen, Golladay, and Davenport (1973) also used linear

programming as the optimization method of choice in studies of

optimal health manpower staffing. George, Fox, and Canvin (1983)

used a linear programming model to identify the optimal

throughput of patients, taking into account their urgency,

diagnosis and resource use, and the availability of resources.

These studies, although few in number, demonstrate the elegance

and parsimonious nature of this quantitative technique. The use

of linear programming is particularly relevant to an examination

of optimization in the MHS.

Purpose

The purpose of this project is to determine why the

Internal Medicine clinic is not meeting access to care

standards. This study will also identify ways to improve

beneficiary access in the IM clinic by determining the maximum


number of patients that can be served given the constraints

facing the clinic. Additionally, this study will seek to

determine methods and procedures to improve clinical business

practices in an attempt to increase beneficiary access.

Methods and Procedures

The methods and procedures utilized in this study include

gathering secondary data from a wide range of information

systems established in the MHS, providing descriptive statistics

that include central tendencies and ratios, and using a linear

programming model. Two major sections are used in the

organization of my analysis. First, under the supply of care

section, I include (a) the Innova Group Analysis, (b) estimating

the supply of care, (c) support staff and exam rooms to provider

ratios, (d) linear programming model, and (e) provider

productivity analysis. Under the demand for care section, I

include (a) enrollment capacity, (b) estimating beneficiary

visits, (c) estimating demand for care, (d) appointment wait

time analysis, and (e) access to care metrics.

The Innova Group Analysis and supply of care estimates are

used to forecast staffing requirements in the IM clinic and to

show if the IM clinic is postured to meet the demand of its

beneficiaries with the staff at hand. Next, the support staff

and exam room ratios will be presented. These ratios will


indicate if the IM clinic has the appropriate number of support

personnel to assist providers in meeting the demand and if

sufficient exam rooms exist to serve its beneficiaries. A linear

programming model is introduced next. This model provides a

method of determining the optimal number of providers required

for a given population under existing operational constraints.

Finally, provider productivity based on relative value units

(RVUs) in the IM clinic will be presented.

The enrollment capacity of the IM clinic will be analyzed

by utilizing the MEDCOM Enrollment Capacity Model. The

enrollment capacity analysis will show if the IM clinic is under

or over its beneficiary capacity. Additionally, analyses of the

demand for care and estimated beneficiary visits per year will

show how frequent the population enrolled in the IM clinic uses

its services. Finally, appointment wait time data and access to

care metric from the Composite Healthcare System (CHCS) and the

Patient Administration System and Biostatistics Activity (PASBA)

will be supplied. Wait time and access to care data will provide

an indication of how the IM clinic is meeting the needs of its

beneficiaries in a timely manner.


Supply of Care

Innova Consulting Group Analysis

In May 2000, the Innova Consulting Group conducted an

analysis through collaboration and work sessions with senior

staff from each department. The group made recommendations

related to operational changes and future scenarios based on

anticipated changes in population, workload and staffing

forecasts. Staffing forecasts were developed based upon expected

levels of provider productivity. The Innova Consulting Group

evaluated provider productivity given (a) available clinic hours

per day, (b) available clinic days per week, (c) available

procedure days per week, (d) average visits per hour, and (e)

average provider visits per year.

Estimated Supply of Care

The estimated supply of care, or throughput, is based on

number of appointments,3 in a period of one year, available per

PCM FTE in the IM clinic.

3 Only urgent, routine, follow-up, and initial visit types

of appointments were considered in this study.


Support Staff and Exam Room Ratios

MEDCOM calculates clinical support staff ratios based on

three-to-one support staff per provider. The three-to-one factor

is then multiplied by the FTE factor per provider that will

result in the target support staff required per provider. This

figure is then multiplied by the average annual cost per support

staff employee ($47,500) that results in the amount of dollars

required to plus up the staff to a 3:1 ratio.

The goal of exam room per PCM ratio is calculated based on

two-to-one exam rooms per provider. The total number of exam

rooms per PCM FTE is then divided by the total number of FTE

PCMs available (MEDCOM, 2002).

Linear Programming Model

Linear programming is one of several quantitative

techniques that organizations can use to determine optimal

values to inform decision making and solve management problems

(Austin & Boxerman, 1995). The use of this model provides a

method of determining the optimal number of providers required

for a given population under existing operational constraints.

In the development of this model for the current project, I

assumed linearity in the constraints presented and developed in

the linear programming appointment model (LPAM).


Provider Productivity

The use of a resource-based relative value scale (RBRVS)

allows procedures and costs to be identified on a common or

relative basis, using relative value units (RVUs; Shackelford,

1999). Relative value units can be used to develop, evaluate,

and allocate resource requirements for a particular organization

(Burger, 2001). Work RVUs, in particular, represent the amount

of time, effort, and intensity required by physicians to perform

services and procedures. The RVU also includes practice and

malpractice expense. As utilized in the MHS setting, RVUs do not

include practice and malpractice expenses (Glass, 2002).

Demand for Care

Enrollment Capacity

The capacity calculation is operationally defined as the

number of patients to be empanelled/enrolled by full time

equivalent (FTE) providers (MEDCOM, 2002). FTE is defined as an

adjusted fraction of the time an employee, working in a primary

care setting, is actually available to provide care for

beneficiaries (LTC G. Patrin, personal communication, September

10, 2002). The enrollment capacity calculation assumes that a

provider has three clinical support staff and two exam rooms

available. The model also assumes that providers are available


for 52 weeks for direct patient care, work 37.5 hours per week,

and conducts three patient visits per hour.

Enrollment capacity hinges upon (a) the average active duty

intern population assigned to the MTF, (b) the current TRICARE

Prime enrolled population, and (c) the number of non-TRICARE

Prime users (beneficiaries that have used the MTF three times or

more) (MEDCOM, 2002). Summing the total number of beneficiaries

in each category provides total required empanelled population.

Also, the internal medicine clinic uses appointment templates as

a means for developing the number of weekly appointments. These

templates are based on the number and type of providers

(physician, registered nurse or physician assistant) and their

availability to provide beneficiary care (MEDCOM, 2002).

Estimated Demand for Care and Beneficiary Visits

The demand for health care depends upon age, sex, and

health status of the enrolled population (MEDCOM, 2002). To

capture demand, many organizations use utilization of services

as a proxy for this construct. Within the MHS, demand is based

on four outpatient visits per year per beneficiary as calculated

in the Enrollment Capacity Plan (ECP) developed by MEDCOM.

Beneficiary visit estimates are critical in determining the

overall demand for care in the IM clinic. These estimates will


determine how many times the enrolled population seeks care in

the IM clinic.

Appointment Wait Time and Access to Care Metric

In and effort to improve access to care for beneficiaries,

TRICARE has developed methodologies to standardize the

appointment system. The objectives of appointment

standardization include (a) improvement of beneficiary customer

service, (b) simplification of the appointing and referral

process, and (c) increased involvement of the managed care

support contractor (MCSC) in the appointing process (DoD TRICARE

Management Activity, 2001). The access standards for

appointments established by TRICARE are as follows: 24 hours

for acute appointments, 7 days for routine appointments, and 28

days for wellness and specialty appointments. One method of

measuring access is to calculate the number and percentage of

appointments scheduled within the standards detailed above. This

method will facilitate an analysis of how well a facility is

meeting access standards by capturing those appointments outside

the standard. The goal is to meet appointment standards with at

least 90% compliance of total appointments in a specific

category (PASBA, 2003).

After collecting and analyzing the data, I will develop a

list of business initiatives to address problems and improve the


status quo by optimizing operations and improving productivity

within the IM clinic.

Data Sources

The Composite Healthcare System (CHCS) was used to

determine the total number of patient visits in the IM clinic.

Active duty and TRICARE Prime data were extracted from the CHCS

database and examined to determine the total number of TRICARE

Prime patient visits. The MHS Management Analysis and Reporting

Tool (M2) database and the Patient Administration System and

Biostatistics Activity (PASBA) were queried to obtain the number

of TRICARE Prime enrolled beneficiaries and the access to care

compliance in the IM clinic. The data collection period was from

October 1, 2001 through September 30, 2002. The data used in

this study were aggregated and did not have personal identifiers

attached; therefore, obtaining consent from individuals was

unnecessary.

Validity is the ability of a research instrument to measure

what it is supposed to measure. Reliability is the ability of a

research instrument to measure what is designed to measure in a

consistent manner (Cooper & Schindler, 2001). The validity of

the construct known as optimization is based on logical

validity. By selecting appropriate data elements that measure

beneficiary access, a reasonable connection can be made between


the data and the construct of optimization.

Minimization of systematic errors in data retrieval and

processing substantially increases reliability. The MHS has

instituted a comprehensive program of identification, monitoring

and improvement strategies for the full range of data quality

issues. This data quality (DQ) program ensures accurate and

timely data capture in all MTFs through the utilization of a DQ

managers and DQ committees to audit and troubleshoot any DQ

issues (PASBA, 2003). Additionally, clerical and administrative

personnel that use the CHCS and other information systems

receive periodic formal and ongoing informal training on data

entry and other aspects of information management, which reduces

the potential for errors. The MHS DQ programs and committees and

the implementation of periodic data entry training to minimize

random or unstable errors, make data collecting systems in the

MHS reliable.

Results

Supply of Care

Innova Consulting Group Results

The results of the Innova Consulting Group analysis are

presented in Table 1.


Table 1

Internal Medicine Clinic Average Provider Availability in FY

2002

Weeks/Year Hours/Year

Annual Compensated Time 52 2,080

Reason for Absence

Annual Leave -4 -160

Sick Leave -2 -80

Holidays -2 -80

Continuing Medical Ed. -1 -40

Military Training -1 -40

Training holidays -0.8 -32

TOTAL AVAILABLE TIME 41.2 1,648

________________________________________________________________

Table 1 shows an estimated total of 1,648 clinic hours for

military providers. The Innova Consulting Group did not allocate

military training (40 hours) for civilian providers. This

resulted in 1,688 available hours per year for civilian

providers. One additional and critical factor that impacts the

IM clinic is the daily duties that internists must perform as

hospitalists. A hospitalist is defined as an internist

performing on call duties for inpatient care. These duties

include regular cardiac stress tests, nuclear medicine stress

tests, pre-operation EKG evaluations, and urgent inpatient

consults. The IM clinic has an internist performing inpatient

hospitalist duties seven days per week. A hospitalist

internist’s duty schedule sample is presented in Figure 1.


While performing these duties, these internists are not

available in the clinic to see patients on an outpatient basis;

therefore, these duties reduce the overall FTE provider

availability in the clinic by at least one full FTE.

Current Format

Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday

Hosp 1

Backup 1

Backup 2

Backup 3

New Hosp

Proposed Format

Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday

Hosp 1

Backup 1

Backup 2

Backup 3

New Hosp

Legend

0730 0730

0730 0730

0 7 3 0

16 3 0

16 3 0

0 7 3 0

0 7 3 0 0 7 3 0

0 7 3 0

16 3 0

0 7 3 0

0 7 3 0

16 3 0

0730 0730

16 3 0 0 7 3 0

0 7 3 0

16 3 0

16 3 0

0 7 3 0

0 7 3 0 16 3 0

0 7 3 0 0 7 3 0

16 3 0

0 7 3 0

0 7 3 0

16 3 0

0 7 3 0 16 3 0

16 3 0

0 7 3 0

0 7 3 0

16 3 0

Provider Away from the clinic (No Appointments)

Provider in the clinic (Only half day)

Provider off-duty

Figure 1. Current and proposed hospitalist schedule for the

Internal Medicine Clinic.________________________________________________________________

Estimated Supply of Care

The estimated supply of care, or throughput, is based on

number of appointments, in a period of one year, available per

PCM FTE in the IM clinic. At the end of FY 2002, the IM clinic


had 9.7 FTE permanently assigned PCMs. Two of these PCMs were

contract providers hired through the MCSC resource sharing

agreement. Currently, the IM clinic builds its PCMs’ templates,

minus two resource share providers, with appointment slots of 30

minutes each. For providers working under resource sharing

agreements, templates are built based on 20-minute appointments.

Utilizing the Innova Consulting Group model in Table 1, which

accurately depicts the current status of IM personnel (LTC L.

Tucker, personal communication, January 15, 2003) results in an

estimated total of 36,419 appointments available per year in the

IM clinic (see formula below).

Total appointments per year:

[(Military Provider FTE) X (1,648 available hours) X

(# of appointments/hour)]+ [(Contract Provider FTE) X

(1,720 available hours) X (# of appointments/hr)] +

[(GS civilian provider FTE) X (1,720 available hours) X

(# of appointments/hour)]

Support Staff and Exam Room Ratios

Additional factors that affect the ability of a PCM to see

patients at a given period are the support staff and exam room

to provider ratios. The DoD’s Population Health Improvement


Guide suggests an optimal support staff ratio of 3.0 to 3.5 per

full time equivalent PCM. The Automated Staff Assessment Model

(ASAM) III recommends a staff support ratio of 2.8 per PCM FTE

based on budgetary constrains. Table 2 presents ratios of

support staff to provider FTEs, as well as current provider and

support staff FTEs, for personnel assigned to the IM clinic,

family practice, and pediatrics. Table 2 shows that the IM

clinic has a support staff to provider ratio of 1.6 which is the

highest of all three primary care clinics, but still lower than

the MEDCOM’s target ratio of 3:1.

Table 2

Primary Care Clinics Average Support Staff to Provider Ratios in

FY 2002

Clinic Provider FTE Support Staff Ratio

IM 9.7 15.0 1.6Family Practice 12.0 24.0 1.5Pediatrics 8.5 10.5 1.3________________________________________________________________

Exam rooms to provider ratios directly affect the total

number of beneficiaries that can be seen by their PCMs in an

hour. Table 3 provides the ratios of all three primary care

clinics, which are physically collocated. The collocation of

exam rooms is important not only because of sub-organizational

interdependence, but also because these rooms may be shared or


otherwise utilized in order to increase productive efficiency of

the clinics.

Table 3

Primary Care Clinics Average Exam Room to Provider Ratios in FY

2002

Clinic Provider FTE Exam Rooms Ratio

IM 9.7 19 2.0Family Practice 18.0 38 2.1Pediatrics 8.5 15 1.8________________________________________________________________

Linear Programming Appointment Model

In order to examine the relationship between numbers of

providers, type of appointments, and appointment utilization, I

developed a simple linear programming appointment model (LPAM)

and employed graphical and algebraic techniques to determine the

maximum number of appointments that the clinic could provide

given organizational constraints. Results of this model are

depicted in Figure 2. The LPAM arrived at the following

equation:

Maximize: X1 + X2 = P (Appointments)

.5X1 + .3X2 < 77.6 (Labor hours constraints)

.5X1 + .3X2 < 77.6 (Exam room constraints)

.5X1 + .3X2 < 41.1 (Support staff manpower hours constraint)

X2 < 48 (Contract provider hours constraint)

X1 > 0, X2 > 0 (Nonnegativity constraints)


Where P represents the total number of appointments available

per day, X1 represents the number of 30-minute appointments

available per day, and X2 represents the number of 20-minute

appointments available per day. X1 and X2 are the decision

variables. The labor and exam room hour constraints are

calculated by multiplying the total provider FTE in the IM

clinic (9.7) times the hours in a normal work day (8.0). The

support staff manpower hours constraint is calculated by

multiplying the total provider FTE in the IM clinic (9.7) times

the hours in a normal work day (8.0), times the support staff to

provider ratio (1.6), then divided by the optimal support staff

to provider ratio (3.0). Lastly, the contract provider

constraint is calculated by multiplying the total contract

provider FTE (2.0) times the hours in a normal work day (8.0)

times total 20-minute appointments available per hour (3.0). A

visual inspection of the LPAM shows that the optimal solution is

a corner solution that equates to 48 20-minute appointments and

53 30-minute appointments per clinic day. The provider and exam

room hour constraints do not affect the ability of the IM clinic

to see more patients. However, the support staff constraint

prevents the IM clinic from increasing appointments without the

hiring of more support staff.


50 100 150 200

X1 (Number of 30-minute appointments)

X2(Number of 20-minute appointments)

X2< 48 (Contract providers)

.5X1+.3X2<77.6 (Providers hours)

.5X1+.3X2<41.1 (Support staff manpower hours)

.5X1+.3X2<77.6 (Exam room hours)

250

200

150

100

50

Figure 2. Graphic representation of support staff manpower

constraint per clinic day (.5X1 + .3X2 < 41.1), GS/civilian and

military provider hours constraint per clinic day (.5X1 + .3X2 <

77.6), Exam room hours constraint per clinic day (.5X1 + .3X2 <

77.6), contract provider hours constraint per clinic day (X2 <

48) as they impact the supply of 30-minute (X1) and 20-

minute (X2) appointments in the IM Clinic.

________________________________________________________________


Provider Productivity

Lastly, I looked at provider productivity for the IM clinic

based on relative value units (RVUs). Relative value units

provide a measurement of clinic productivity based on the acuity

of patients. Table 4 provides a comparison of RVUs between the

IM clinic, family practice, and pediatrics clinics for FY 2002.

When compared with other primary care clinics at EACH, the IM

clinic produced the lowest encounter adjusted RVUs based on the

acuity of its patients.

Table 4

Primary Care Clinics Average Relative Value Units in FY 2002

Clinic Encounters RVU Mean RVU/Encounter

Internal Med 49,920 28,011 0.56Family Pract. 73,600 48,136 0.65Pediatrics 15,272 11,392 0.75________________________________________________________________

Another comparison is presented in Table 5 between EACH and

other MTFs with similar size and enrolled population. Data

presented in this table pertains only to IM clinic at each

facility for FY 2002. Once again, the IM clinic at EACH showed

the lowest mean RVU when compared with other facilities of

similar size.


Table 5

MTF Average Relative Value Units Comparison in FY 2002

MTF Encounters RVU Mean RVU/Encounter

Ft. Carson 49,920 28,011 0.56Ft. Benning 23,833 14,024 0.59Ft. Jackson 18,557 13,893 0.75Ft. Belvoir 63,928 37,007 0.58________________________________________________________________

Demand for Care

MEDCOM Enrollment Capacity Model

The purpose of the MEDCOM enrollment capacity model is to

accurately forecast the enrollment capacity for primary care

providers and their support staff. If applied, this model will

help guide the primary care clinics into doing the best they can

with available resources against predetermined quality

standards, business processes, and customer satisfaction.

According to the MEDCOM enrollment capacity model, the

appropriate panel size for a PCM working full time 1.0 FTE is

1,178 beneficiaries. This panel size is further reduced based on

a 2.5 factor assigned to each beneficiary over the age of 65.

The over the age of 65 beneficiaries number is multiplied by the

2.5 factor to compensate for the additional time and health care

requirements this population demands from the IM clinic. Table 6

depicts the results for the IM clinic’s PCMs by beneficiary


category and shows inflated numbers for the over the age of 65

population.

Table 6

IM Clinic Average Enrollment Capacity by Beneficiary Category in FY

2002

PanelPCM FTE Size AD ADD NADD >65a Total Percent

1 Chief (Mil)0.5 589 4 54 258 523 839 142

2 Military 0.2 236 2 29 71 73 175 74

3 0.5 589 4 38 427 920 1,389 236

4 0.5 589 0 83 213 218 514 87

5 Military 1.0 1,178 1 100 366 695 1,162 99

6 Military 1.0 1,178 2 85 348 665 1,100 93

7 1.0 1,178 0 42 315 790 1,147 97

8 1.0 1,178 1 76 354 668 1,099 93

9 1.0 1,178 1 67 309 793 1,170 99

10 1.0 1,178 0 38 315 593 946 80

11(Contract) 1.0 1,178 0 97 362 0 459 39

12(Contract) 1.0 1,178 0 62 250 0 312 26

TOTAL 9.7 11,427 15 771 3,588 5,938 10,312 90

________________________________________________________________

Note. AD = active duty; ADD = active duty dependent; NADD = non-active

duty dependent; >65 = over the age of 65.aThe >65 figures include a 2.5 factor per beneficiary.

Table 6 shows that several providers are under capacity and

two providers are over capacity based on their panel size

allocations. In addition to the enrollment capacity table for

the IM clinic, enrollment data for the other two primary care

clinics are presented in Table 7 for comparison purposes. Table

7 clearly shows that the IM clinic has a larger population of

over the age of 65 than the family practice clinic.


Table 7

Primary Care Clinics Average Enrollment Capacity by Beneficiary

Category in FY 2002

ProposedClinic FTE Capacity AD ADD NADD >65 Total Percent

Family P. 16.5 19,490 1,059 13,641 4,598 1,030 20,330 104IM 9.7 11,427 15 771 3,588 5,938 10,312 90PEDS 4.5 5,301 0 5,671 782 0 6,453 122______________________________________________________________________


duty dependent; >65 = over the age of 65.

Estimated Beneficiary Visits per Year

Another key factor to consider in analyzing clinic capacity

is to determine how many times beneficiaries seek care in the IM

clinic. Table 8 provides the total number of visits by

beneficiary category, the mean number of per person visits by

category, and the percentage of visits attributed to a

particular category. A tremendous amount of variation exists

across categories. The NADD and the over the age of 65

beneficiaries took 87.6% of all visits in FY 2002. By contrast,

the active duty population and their dependents took only 12.4%

of the visits in FY 2002.


Table 8

Average Beneficiary Visits in Internal Medicine Clinic FY 2002

by Category

Category Visits Mean Percent

AD 1,184 2.4 2.6

ADD 4,536 4.1 9.8

NADD 21,409 5.6 46.4

>65 19,013 7.9 41.2__

Total 46,142 6.3 100.0

________________________________________________________________


duty dependent; >65 = over the age of 65.

Estimated Demand for Care

The estimate of demand for care shows the total number of

beneficiaries assigned to each PCM, by category who are enrolled

in the IM clinic. This data, in conjunction with the total

visits by beneficiary category, provide another approach in

helping determine the capacity of the clinic and prioritize

future enrollments. The IM clinic has a total enrolled

population of 10,312 beneficiaries with a weighted average visit

per beneficiary of 6.3 visits. This total includes active duty

(AD), active duty dependent (ADD), non-active duty dependent

(NADD), and the over the age of 65 (with 2.5 factor)

beneficiaries categories.


Appointment Wait Time

Template Management

At the present time, the IM clinic manages its provider’s

templates by utilizing four types of appointments: acute,

routine, established (follow-up), and PCM (initial visit). The

length of each appointment is set at 30 minutes each regardless

of beneficiary age or type of appointment. Resource share

providers, on the other hand, have 20-minute appointments across

the board regardless of beneficiary age (minus age 65 and over

beneficiary), and type of appointment. At any given day, the IM

clinic has a maximum of 182 appointments available and a minimum

of 150 appointments based on the number of 30-minute or 20-

minute appointments available per day.4 This availability of

appointments is also based on the available FTE per provider

when all providers may be present for duty at one time or

unavailable based on their assigned FTE factor on an 8-hour

working day.

4 These figures do not consider the negative effect of

support staff shortages.


Access to Care Metric

The access to care metric determines the responsiveness

(compliance) of the clinic’s patient care in terms of whether or

not urgent and routine appointments meet TRICARE access

standards. Table 9 depicts access to care data collected on

EACH’s IM clinic from the U.S. Army Patient Administration

Systems and Biostatistics Activity (PASBA) in FY 2002. PASBA

utilizes CHCS data and extracts the following formula to assess

a specific clinic against access standards:

(Total # of Appointments within standard X 100) /

(Total # of Appointments Requested)

Table 9

FY 2002 Access to Care Metric Results

Urgent Appointments Routine Appointments____

Month Total Compliant Percent Total Compliant Percent

OCT 325 232 71 621 276 44NOV 353 232 66 645 250 39DEC 328 224 68 562 247 44JAN 420 287 68 792 365 46FEB 371 256 69 600 225 38MAR 368 242 66 455 146 32APR 412 293 71 556 190 34MAY 288 260 90 262 137 52JUN 281 231 82 90 70 78JUL 257 193 75 124 102 82AUG 329 257 78 162 133 82SEP 277 247 89 193 120 62________________________________________________________________


Table 9 shows that the IM clinic failed to meet access to

care standards for urgent appointments 11 out of 12 months in FY

2002. It also shows the clinic failed to meet access to care

standards for routine appointments every month in FY 2002.

Discussion

One of the greatest constraints in improving the IM

clinic’s ability to meet access to care standards is the lack of

effective provider’s time and template management. The IM clinic

is not at its maximum capacity for enrolling beneficiaries.

Applying the MEDCOM enrollment capacity model, the IM clinic

currently sits at 90% of its total beneficiary capacity. Some

providers have greater than optimal enrollment panel sizes, and

others have less than optimal numbers. For example, one provider

maintains a panel size that is 136% over ideal capacity. Prior

to this research, provider capacity in IM, and in all the

primary care clinics, has not been established and

scientifically analyzed in order to effectively optimize

providers’ beneficiaries enrollment panels.

Also, prior to this research, accurately allocating FTEs

to each provider assigned to the IM clinic has never been

accomplished. The personnel division at EACH calculates FTE

allocations for civilian employees but it does not reflect the

actual FTE once a provider is permanently assigned to the

clinic. This FTE assessment is accomplished in a combined effort

between the clinic chief, careline chief, clinical operations

division, and the personnel division based on the actual duties


and responsibilities of each provider. Once this process is

accomplished, an accurate FTE allocation could be determined to

reflect actual provider availability.

One of the clinic’s providers is a full time civilian

employed provider who, because of his additional

responsibilities of running other educational programs for the

facility, is unable to be 1.0 FTE for the IM clinic. Therefore,

beneficiaries assigned to this provider have difficulty in

seeing him on a timely basis due to over-empanelment.

Availability is also affected by the hospitalist duty

schedule, which two providers are absent from the clinic two

days every week. Regardless if a hospitalist internist is called

in the night before to perform on call duties, he or she takes

one half day off (Tuesday through Thursday) the following day.

Also, the hospitalist internist on call on weekends and

Thursdays takes the following day off regardless if he or she

was called in the day prior. Additionally, three days of every

week 1.5 provider FTEs are absent from the clinic.

Another finding in the enrollment capacity analysis is the

under empanelment of two resource share contract providers.

These contract providers are 1.0 FTE for the clinic but their

current panel sizes do not reflect their ability to accept a

larger population of beneficiaries. Currently, these two

contract providers have only 39% and 26% of their proposed

empanelment capacity.

The estimated beneficiary visits per year are also


important considerations when optimizing the IM clinic. The

older population, over the age of 65, presents some unique

challenges. This population visits the facility more often than

any other beneficiary category seeking healthcare for chronic

illnesses (LTC L. Tucker, personal communication, January 15,

2003). The population over the age of 65 had a mean of 7.9

visits per beneficiary in this category in FY 2002. Current

estimates for military visits rates to primary care range from

four to five visits per enrollee per year (DoD TRICARE

Management Activity, 2001). This finding becomes critical as the

IM clinic attempts to adjust its 30-minute appointment templates

to accommodate longer than usual appointments for this

population and to estimate the demand for care.

In order to achieve high levels of effectiveness in

improving access to care, the IM clinic must manage its health

resources and have an accurate account of the enrolled

population. At present time, the IM clinic has 10,312

beneficiaries distributed in different categories. Is this

population of beneficiaries above or below the capacity of the

IM clinic? According to the MEDCOM enrollment capacity model,

the IM clinic is under capacity by 10%. This conclusion is not

enough to answer the research question of meeting access

standards. Therefore, I looked into other factors that may

affect the ability of the IM clinic in meeting access to care

standards.

Considering the Innova results of estimating provider


availability, in tandem with the total beneficiary visits in FY

2002, one can identify a shortage of available appointments. By

estimating 32,403 appointments, based on 9.7 provider FTEs in FY

2002, against 46,142 total visits in FY 2002, there is a deficit

of 13,739 appointments. Consequently, beneficiaries had to wait

longer than the established access to care standards in FY 2002

to see their PCMs.

In the support staff to provider ratio results, the IM

clinic still lacks sufficient support staff. In accordance with

the MEDCOM guidance of optimal support staff to provider ratio

of 2.8 to 1, the IM clinic needs to increase its support staff

to a level closer to the suggested 2.8 per provider FTE. At

present time, the IM clinic has a 1.6 support staff to provider

FTE ratio. This will positively impact the ability of providers

to dedicate more time to patient care rather than spend time

performing administrative duties that support staff is designed

to accomplish.

Analyzing the exam room to provider FTE ratios, the IM

clinic fares well with the MEDCOM guidance of 2.0 to 1 ratio.

The rest of the primary care clinics are also at or just below

the optimal ratio.

Providers' templates are perhaps the factor that has the

most profound effect on the clinic's throughput. All military

and government service (GS) providers have their appointments

set for 30 minutes each regardless of the type of patient. This

decision was made at the start of FY 2002 when TRICARE senior


prime took effect to provide adequate provider-to-patient

encounter time to the over the age of 65 beneficiaries.

Certainly, this approach benefits this population, which

represents more than 50% of the total enrolled population in the

IM clinic, and also takes approximately 41% of all visits.

However, it should not exclude the rest of the enrolled

population, which does not need the extended 30-minute

appointments (LTC(P) L. Tucker, personal communication, January

15, 2003). By contrast, contract providers have 20-minute

appointments, but they are restricted from seeing over the age

of 65 beneficiaries.

A linear programming model was utilized to offer an

alternative to managing appointments in the IM clinic based on

total appointment, support staff, exam room, and provider

constraints. This model shows how support staff and exam rooms

constraints and their impact on the appointment supply in the

clinic. Based on this model, the optimal point is depicted by

the intersection of the support staff and contract provider

constraint lines. This optimal point results in 48 20-minute and

53 30-minute appointments may be booked every clinic day without

affecting efficiency. The model also shows that before the

clinic’s leadership decides to expand or increase appointments,

the hiring of support staff must be accomplished. If continued

expansion and increase of appointments become necessary after

hiring additional support staff, space availability will have to

be addressed to maintain efficiency. This model will prove


helpful when maximizing and properly managing provider templates

by assigning a balanced number of 20 and

30-minute appointments.

The access to care metric plays an important role in the

optimization process of the IM clinic. This metric is tracked,

at the corporate level, through the U.S. Army Patient

Administration Systems and Biostatistics Activity (PASBA). This

provides a snapshot by month of the MTF’s access to care

compliance status of urgent and routine appointments. During FY

2002, EACH’s IM clinic met access to care standard only 8% of

the time, under the urgent appointment tracking statistics.

Relative value units (RVU) provide a quantitative means for

tracking provider productivity. By tracking RVUs against

encounters between providers and patients through appropriate

coding, organizations can identify the intensity of the

encounter and demonstrate that providers are working at a higher

skill level. The overall IM clinic’s RVUs were compared with the

rest of the primary careline. The comparison shows that despite

the high number of over the age of 65 population enrolled in the

IM clinic, RVUs per encounter were the lowest of all three

primary care clinics. Proceeding one step further, a comparison

between EACH’s IM clinic and other three MTFs’ IM clinics of

similar size and enrolled population shows EACH's IM clinic has

the lowest RVUs. These results counter the argument that the IM

clinic's providers are working more intensely with more complex

patients.


Recommendations

Based on the results of this study and analysis of the data,

an immediate provider empanelment reorganization of the Internal

Medicine clinic would provide the momentum for improving

productive efficiency of the clinic. This action alone will have

a direct and immediate positive effect in meeting access to care

standards. This reorganization will provide beneficiaries

enrolled in the IM clinic the opportunity to access their

assigned PCMs more expeditiously, which will decrease average

appointment-waiting times.

Additionally, the organization may consider the following

recommendations to improve the healthcare delivery operations of

the Internal Medicine clinic:

1. The IM clinic should determine the extent to which

assigned providers are available to provide direct patient care

(i.e., determine actual FTEs). This assessment should include an

analysis of all duties and responsibilities of the providers to

determine if these duties outweigh the need to provide better

access to the beneficiaries. Before this study, an assessment of

providers’ FTEs had not been accomplished. Previously, all

providers were assigned as a full (1.0) FTE. The lack of

accurate FTE assessments encourages TRICARE enrollment personnel

to erroneously assign beneficiaries to providers who are not

available on a full time basis.

2. I recommend that providers and organizational leadership

conduct an analysis of all beneficiaries’ records in order to


match beneficiaries and providers. Matching on the basis of

patient characteristics and provider capabilities may reduce the

assignment disparity that exists between and within departments.

As shown in the results, a large disparity exists between some

providers who are not considered 1.0 FTE but have overpopulated

panels. Also, a larger disparity between contract providers and

regular staff providers’ panels exists. Since contract providers

are restricted from seeing over the age of 65 patients due to

federal reimbursement conflicts between Medicare and MTFs, it is

appropriate to distribute and assign the younger beneficiary

population to these providers. As shown in the results, both

contract providers remain at 39% and 26%, respectively, of their

proposed panel size capacity.

3. I also recommend a redistribution of the over the age of

65 population between the IM clinic and the family practice

clinic. Currently the IM clinic holds approximately 85% of the

over the age of 65 population enrolled at EACH. The less serious

and younger patients from this population should be exchanged

with other beneficiaries from the family practice clinic. This

redistribution should bring a better balance of this population

between the clinics, which would provide more time and

flexibility to the IM clinic in managing providers’ templates

and length of appointments.

4. The organization should review and revise its hospitalist

duty schedule. This process should include the clinic chief, the

careline chief, and the deputy commander for clinical services.


The IM clinic loses approximately 62 provider hours per week due

to the performance of these duties. This obviously equates to

less appointments available at the clinic. This proposed

schedule allows for provider recovery time with only 46 provider

hours away from the clinic. Additionally, a better compensatory

time tracking mechanism should be in place to not only protect

the staff providers from fatigue, but maximize provider

availability if actual on-call duties were performed. If

hospitalist providers on call are not called in, these providers

should be present for duty the following day. This rule should

be applied to all providers regardless if they are military or

government service civilians. This researcher also recommends

periodic audits of the clinic’s compensatory time practices.

5. A support staff to provider ratio analysis should be

further investigated. Support staff resources remain at critical

levels across all primary care clinics. The IM clinic’s support

staff to provider ratio is at 1.6. This figure is well below the

recommended ratio from the PHI guide and MEDCOM. Time and effort

should be dedicated to invest and hire more support staff to

optimize patient-to-provider time. Contrary to perceptions held

by the clinic’s leadership, the results of this study suggest

that enrollment capacity, panel redistribution, duty schedules

and template management also play a tremendous role in limiting

access to care. The lack of providers, a factor that initially

drove the primary care optimization business case analysis that

was submitted to MEDCOM in 2001, is neither the key nor sole


factor that limits productive efficiency in the IM clinic.

6. A revision of provider templates should be accomplished

at the earliest opportunity. Provider templates are a critical

factor in scheduling patients and optimizing the productivity of

providers. Currently, templates are built based on 30-minute

appointments for acute and routine encounters regardless of the

age of the patient. The premise for this extended length of

appointment times is to compensate for the medical needs of the

older population, which consume more time per encounter when

compared with other age groups. This researcher recommends the

establishment of a mixture 20 and 30-minute appointments during

an optimization transition period. Once the above

recommendations have been executed, then all appointments should

be for 20 minutes. If more time is needed for first time

beneficiary appointments, then two 20-minute appointments should

be combined to accommodate an appropriate assessment of the

patient by the provider.

7. The proper utilization and standardized training of the

support staff should be examined more closely. Tasks performed

by the support staff are not standardized across the clinic.

Some administrative tasks that should be performed by the

support staff are being accomplished by the providers.

Therefore, providers spend their valuable time performing

administrative tasks that otherwise should have been

accomplished by the support staff. A further examination of

support staff training and utilization may be helpful in


improving efficiency.

8. Providers’ productivity, based on RVUs, should be part of

the performance improvement objectives in the IM clinic. The

utilization of RVU metrics are highly dependent on coding

accuracy and are the primary driver for reimbursement. I

expected that RVUs in the IM clinic would be higher than RVUs

reported in the other primary care clinics because of the high

number of older beneficiaries enrolled in the IM clinic.

However, the IM clinic at EACH had the lowest RVUs when compared

with other primary care clinics within EACH. Compared with other

similarly sized internal medicine clinics, the IM clinic at EACH

also reported the lowest number of RVUs per encounter. These

findings merit a review of the provider coding accuracy and

further examination of coding personnel procedures.

9. The IM clinic’s leadership should conduct an analysis on

the hours of operations of the clinic. Prior to this study, the

IM clinic started daily operations at 0830. This was due to

avoid conflict of time between their daily morning report

meetings and the start of their first appointment. Starting

operations at 0800 would leave ample time to proceed with their

20-minute morning meeting reports and would ultimately result in

an increase of approximately 130 appointments per month.

Conclusion

The Internal Medicine clinic has the opportunity to

increase its efficiency and productivity in its operations

without incurring a tremendous budgetary burden to the


organization. The key to this optimization initiative rests, not

on the hiring of more providers as previously thought, but on

the proper analysis of actual providers’ FTE figures and proper

distribution of beneficiaries among the providers and between

the family practice and the IM clinics. Another critical factor,

which greatly influences the IM clinic’s ability to increase its

throughput, is the reduction of its appointment lengths from 30

minutes to 20 minutes. If the above recommendations are fully

implemented, the IM clinic will be postured for success in its

effort to increase productivity and meet access to care

standards.

The IM clinic chief has already implemented some of the

above recommendations to optimize clinical operations. He has

changed the clinic’s hours of operations, has initiated

beneficiaries redistributions among all providers, and

reassessed providers’ FTE factors. These changes, coupled with

an ongoing awareness of the factors that limit productive

efficiency and access to care, will undoubtedly improve the

ability of the IM clinic to meet TRICARE’s access to care

standards. The methods and results presented in this study may

be further utilized to optimize the operations of the other

primary care clinics at EACH and increase the access to care of

our beneficiaries.


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Appendix

Primary Care Optimization Business Case Analysis

P OM UFR BCA-FCP L OP TIMIZATION

UFR Submitter/POC MAJ Jim KelleyCommercial Phone 719-526-7473

Activity / Major Subordinate Cmd CSDDate Submitted 05-Feb-01

Unfinanced Requirement (UFR) Description / Return on Investment

Executive Summary

Evans Army Community Hospital (EACH) currently supports 45,732 TRICARE Prime enrollees. Of the 45,732, EACH directly support30,682 of this population. The difference of 15,050 represents the Active Duty soldiers at Fort Carson less the MEDDAC/DENTAC soldieThe figure of 30,682 is approximately 7,000 higher than what the MTF Primary Care Capcity Estimator projects as our current enrollment capacity based on our number of available staff. It is also important to note that we only included those providers in step two of the EstimModel that could be used as PCMs here in the hospital. In a few instances, we had providers who either worked in the Prime Acute CareClinic (after hours clinic) or strictly in the TMCs; therefore, we did not include these providers because they are not used as PCMs for sermembers or other beneficiaries receiving care in the hospital. Instead, these providers along with the FORSCOM medical personnel act aPCMs for the FORSCOM soldiers.

The evolution of TRICARE Senior Prime and continuing efforts to accomodate TRICARE Senior Prime age-ins remains the primary focour PCM capactiy initiatives. As of May 1, 2000, EACH reached its open enrollment target of 2000 enrollees and has also accepted an additional 389 age-ins into the TSP program. We expect the age-in trend to continue and this coupled with the TRICARE For Life programgives us reason to believe more beneficiaries will be seeking to access care in the MTF. Approximately 75% of all enrollees at Fort Carsactive duty and active duty family members. The remaining 25% is comprised of Retirees and their family members as well as the TSP population. It is this population that we are most concerned with because this is where we expect increases in the future. There are exa998 of our eligible beneficiaries enrolled to the network as Civilian Prime. As of this time, we have been able to enroll all eligible beneficiaexcluding the 659 on the TSP enrollment waiting list. Additionally, there are approximately 1,000 Medicare eligible beneficiaries awaitingopportunity to receive an updated TSP enrollment application and to secure enrollment status. In our proposal and both the alternatives, continue to provide care for the MTF enrolled beneficiaries and hope to gain resources to recapture a portion of the 998 currently receivingin the network. It would also be possible given the additional support staff to recapture most if not all of the awaiting TSP population. Significant cost savings occur when recapturing network workload. For example, the average annual claims cost for Civilian Prime is $2,7while the average annual claims cost for MTF Prime enrollees is only $292. If we bring the civilian Prime enrolles back into the MTF, the average annual claim cost for the combined population would be $346.

Perhaps even more important than network recapture would be the opportunity to maximize the care provided in the Primary Care Lineclinics. Obtaining a ratio of 2.8 support staff per provider would most definitely be a step in the right direction. We must offer our providersbest possible clinical environment in order to meet TRICARE access standards. Our proposal and two alternatives follow:

Proposal Primary Care Line (PCL) Model requires additional support staff to increase the efficiency of the PCL. The total cost to hire trequired 2.8 support staff per provider is $1,055,300 annually. This option gives us the opportunity to empanel an additional 9,000 equivalelives or 2,250 patients given the current mix of available beneficiaries. The total cost savings to be realized through this option is $936,21


Unfinanced Requirement Authority / Driver

Additional Impacting FactorsProposal: The average annual claims cost for Civilian Prime is $2,707 while the average annual claims cost for MTF Prime enrollees is only $292. If we bring the civilian Prime enrolles back into the MTF, the average annual claims cost for the combined population would be $346.

The Commander, EACH, received a tasking from BG Perugini indicating we have an opportunity to get real dollars for PCM Primary Care support staff and exam rooms. The CG wants to include this issue as supplemental funding requirements into LTG Peake's testimony to Congress scheduled on 28 Feb 01. In order to meet this requirement, we sumit the following BCA for your review.


Current Funding? Proposal-$ 1,055,300$ -$ -$ -$ -$ -$ 380,700$ -$ ]

Equipment (Non-Procurement) -$ -$ -$ -$ -$ -$ -$ -$ -$ -$ -$ -$

-$ Additional Cost 1,436,000$

-$ -$ -$ 2,372,213$ -$ -$

-$ Savings 2,372,213$ -$ Total Cost/Savings 936,213$

Current Funding? Proposal-$ 1,055,300$ -$ -$ -$ -$ -$ 380,700$ -$ ]

Equipment (Non-Procurement) -$ -$ -$ -$ -$ -$ -$ -$ -$ -$ -$ -$

-$ Additional Cost 1,436,000$

-$ -$ -$ 2,372,213$

UtilitiesMisc

RevenueCost Recapture

New Construction

Unfunded Requirements for FY 2003

RenovationMaintenance

Leases/RentsLabor (as costed from "Manpower" worksheet)

ContractsSuppliesEquipment (Procurement)

SuppliesEquipment (Procurement)

Cost Avoidance

Labor (as costed from "Manpower" worksheet)

Leases/RentsContracts

New ContructionRenovationMaintenanceUtilitiesMisc

RevenueCost Recapture

Unfunded Requirements for FY 2004

Investment

Total Cost/Savings

Investment


Staff FTE Staff FTE Staff FTE

- - - - - - - - - - - - - - - - - - - - - - - - - -

- - - - - -

- - 27.00 27.00 24.00 24.00 - - - - - - - - - - - 5.50 5.50 6.00 6.00 - - - - - - - - - - - - - 32.50 32.50 30.00 30.00 - - 32.50 32.50 30.00 30.00

Staff FTE Staff FTE Staff FTE

- - - - - - - - - - - - - - - - - - - - - - - - - -

- - - - - -

- - 27.00 27.00 24.00 24.00 - - - - - - - - - - - 5.50 5.50 6.00 6.00

Manpower & Staffing Requirements for FY 2003

Current On-Hand Proposal Alternative 1

Military StaffingClinical OfficersClinical EnlistedAdmin OfficersAdmin EnlistedBorrowed Military Providers

Civilian StaffingClinical GSClinical Contract

Admin GSAdmin Contract

Volunteers

Civilian StaffingClinical GS

Total

Manpower & Staffing Requirements for FY 2004

Proposal Alternative 1

Note: Please list, by type of personnel (military, DAC, contractor, etc) and grade all personnel requirements, by year, at the bottom of this wcosted and added to the "Pg 3 Funding & Savings Data" as an investment cost.

Clinical Contract

Admin GSResource Sharing Clinical

Resource Sharing Clinical

Resource Support Admin

Current On-Hand

Military StaffingClinical OfficersClinical EnlistedAdmin OfficersAdmin EnlistedBorrowed


Status Quo Proposal Alternative 1 Alternative 2

Cost to Implement Initiative 1,055,300$ 945,000$ 630,000$

Access for Prime 3 5 4 3

Customer service 3 5 4 3

Customer satisfaction 4 5 4 4

Efficiency and effectiveness 3 5 4 4

Employee satisfaction 3 5 4 4

Overall health care quality 4 5 5 4

Overall Impact 3 5 4 4

Matrix Questions After you have completed the narrative and data portions of the POM UFR BCA please address the following questions. For the cost sectionuse the Total Cost number from the Funding and Savings Data sheet. All the other questions should be scored from 1 to 5. The status quo considered your baseline. The proposal and alternatives scoring should reflect the level of change you expect with the implementation of thePlease be prepared to support your score.

1 = Poor2 = Fair3 = Average4 = Good5 = Excellent


PRIMARY OPTION COSTS AND PERSONNEL

Family Practice Internal Medicine Pediatrics

Enrollees: 17,468 Enrollees: 7,240 Enrollees: 5,974

1 BMM Providers 0 BMM Providers 0 BMM Providers13 MIL Providers 4 MIL Providers 4 MIL Providers1 RS Providers 2 RS Providers 0 RS Providers

6 Civilian Providers 4 Civilian Providers 1 Civilian Providers14.3 TOTAL FTEs 8.7 TOTAL FTEs 3.4 TOTAL FTEs

SUPPORT STAFF SUPPORT STAFF SUPPORT STAFF8 CNAs 2 CNAs 2.5 CNAs5 LPNs 2 LPNs 1.5 LPNs4 RNs 2 RNs 1 RNs

5 Med. Clerks 3 Med. Clerks 1.5 Med. Clerks2 Clinic ADM .5 Clinic ADM .5 Clinic ADM

24 Total 9.5 Total 7 Total

36 EXAM ROOMS 19 EXAM ROOMS 10 EXAM ROOMS

CNAs 25 CNAs 12.5 CNAs 12.5LPNs 20 LPNs 8.5 LPNs 11.5RNs 10 RNs 7 RNs 3

MED CLERKS 15 MED CLERKS 9.5 MED CLERKS 5.5TOTAL 70 TOTAL 37.5 TOTAL 32.5

SUPPORT STAFF COSTS (Required to achieve 2.8 ratio)12.5 CNAs @ $27,100 = $338,75011.5 LPNs @ $33,800 = $388,700

3 RNs @ $59,600 = $178,800

CAPACITY MODEL SUMMARY 0101 TDA SUMMARY NEEDEDSUPPORT STAFF SUPPORT STAFF SUPPORT STAFF


Family Practice Internal Medicine

Enrollees: 17,468 Enrollees: 7,240

1 BMM Providers 0 BMM Providers13 MIL Providers 4 MIL Providers1 RS Providers 2 RS Providers

6 Civilian Providers 4 Civilian Providers14.3 TOTAL FTEs 8.7 TOTAL FTEs

SUPPORT STAFF SUPPORT STAFF8 CNAs 2 CNAs5 LPNs 2 LPNs4 RNs 2 RNs

5 Med. Clerks 3 Med. Clerks2 Clinic ADM .5 Clinic ADM

24 Total 9.5 Total

36 EXAM ROOMS 19 EXAM ROOMS

CNAs 22 CNAs 10 CNAs 12LPNs 17 LPNs 7 LPNs 10RNs 8 RNs 6 RNs 2

MED CLERKS 14 MED CLERKS 8 MED CLERKS 6TOTAL 61 TOTAL 31 TOTAL 30

SUPPORT STAFF COSTS (Required to achieve 2.8 ratio)12 CNAs @ $27,100 = $325,20010 LPNs @ $33,800 = $338,000

2 RNs @ $59,600 = $119,2006 MED CLERKS @ $27,100 = $162,600

SUPPORT STAFF SUPPORT STAFF SUPPORT STAFF

ALT 1 OPTION COSTS AND PERSONNEL

CAPACITY MODEL SUMMARY 0101 TDA SUMMARY NEEDED


Family Practice Internal Medicine

Enrollees: 17,468 Enrollees: 7,240

1 BMM Providers 0 BMM Providers13 MIL Providers 4 MIL Providers1 RS Providers 2 RS Providers

6 Civilian Providers 4 Civilian Providers14.3 TOTAL FTEs 8.7 TOTAL FTEs

SUPPORT STAFF SUPPORT STAFF8 CNAs 2 CNAs5 LPNs 2 LPNs4 RNs 2 RNs

5 Med. Clerks 3 Med. Clerks2 Clinic ADM .5 Clinic ADM

24 Total 9.5 Total

36 EXAM ROOMS 19 EXAM ROOMS

CNAs 19 CNAs 10 CNAs 9LPNs 14 LPNs 7 LPNs 7RNs 6 RNs 6 RNs 0

MED CLERKS 13 MED CLERKS 8 MED CLERKS 5TOTAL 52 TOTAL 31 TOTAL 21

SUPPORT STAFF COSTS (Required to achieve 2.4 ratio)9 CNAs @ $27,100 = $243,9007 LPNs @ $33,800 = $250,600

0 RNs @ $59,600 = $0

SUPPORT STAFF SUPPORT STAFF SUPPORT STAFF

ALT 2 OPTION COSTS AND PERSONNEL

CAPACITY MODEL SUMMARY 0101 TDA SUMMARY NEEDED

internal medicine clinic optimization 1 graduate ... · supplementary notes ... internal medicine...

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